The Discrete Wavelet Transform Based Electrocardiographic Baseline Wander Reduction Method for Better Signal Diagnosis

The algorithms for noise reduction have a significant influence on the performance of all electrocardiographic (ECG) signal-processing systems. This study deals with problems of baseline wander (BW) interference reduction. Reducing this distortion without do forming the signal is difficult. A mixed method is suggested to solve this problem. The zero-phase high pass FIR equiripple filtering approach denoted by (ZPE) and discrete wavelet transform (DWT) correction method (DWTCM) was proposed. ZPE is used at the beginning to filter the signal to a specific level. Then, DWTCM was used for the remaining BW filtration by cutting the drift without ECG wave's distortion. The effectiveness of the proposed method was studied using the percentage root-mean-square difference (PRD) error, the standard deviation of the error, and the signal-to-noise ratio (SNR). The performance of the new method was compared with the other published methods of baseline wander reduction using synthetic as well as the natural signals from the MIT-BIH arrhythmia database. The application of this procedure provided a twofold reduction in the error of the suggested baseline-wander method compared to other methods.